Digital image processing of large format images is often done in parallel for cost efficiency, speed, and reuse of systems (hardware as well as software and image processing algorithms) utilized for processing standard size documents. For instance, wide format scanners need to handle input documents that are up to 36 inches wide or more. In order to make use of existing image processing systems that are designed for regular-size documents (smaller sizes usually up to a maximum of 12 inches wide), or to perform parallel processing to achieve performance goals, it is desirable to divide the input documents into several segments, perform image processing on the segments separately and then stitch the results together at the end to produce a resulting image or document.
However, simply stitching several processed image segments together results in a visible defect at the common boundary(s) and “depletion” artifacts. These artifacts are especially visible when binary (already rendered) parts of the document are put together directly and/or when scanning and printing resolutions differ. A classic example is stitching of two error-diffused images together, where there arises an obvious artifact at the common boundary, as depicted in FIG. 12. There are at least two problems with the image—the artifact at the common image boundary and the “depletion” artifact at the top and bottom of the boundary region, and image boundaries. Artifacts are also visible when anamorphic printing resolutions are used to print the stitched document, such as the case of solid ink printing.
Alternatively, if rendering were performed after stitching the individual segments together, then the rendering module would be expensive because of the memory requirements for processing the larger image portions. Hence, the disclosed systems and methods are directed to various alternative embodiments to reduce the visibility of defects when processing large format images, without increasing the cost of the image-processing pipeline or hardware.
A straightforward method to avoid boundary artifacts is to keep an error buffer with error values at the right edge of the left image and use these error values for the left side of the right image as taught in U.S. Pat. No. 6,282,325 for “Image Processing Technique for Binarizing an Image Scanned by a Shuttle Type Scanner,” issued Aug. 28, 2001 to Ji-Hoon Han, and U.S. Pat. No. 4,958,236 for an “Image Processing Method and Apparatus Therefor,” by Nao Nagashima, et al., issued Sep. 18, 1990. Such a method could be fairly costly, however, and requires specialized hardware and complicated image manipulation.
Another method to avoid or reduce artifacts is to modulate the error diffusion threshold at the boundary as disclosed by Zhen He et al., in “Boundary Stitching Algorithm for Parallel Implementation of Error Diffusion”, pp. 344-355, in Color Imaging IX: Processing, Hardcopy, and Applications, (Reiner Eschbach, Gabriel G. Marcu editors), held in San Jose, Calif., Volume 5293, No. 5293, published by SPIE and IS&T in 2004. This method requires a specialized threshold modulation circuit.
Generally, the depletion artifact causes corners to be rounded and dots to be “aligned”. This defect type may be avoided by using a different threshold in highlight regions as taught in U.S. Pat. No. 6,285,464 for an “Apparatus and Method for Producing a Half-tone Image,” by Akihiro Katayama, et al., issued Sep. 4, 2001. U.S. Pat. No. 4,958,236 proposes parallel processing by dividing the image into equally overlapping or overlapping to the left/right only segments, and also passing the error to the next band. This method requires scanline buffers storing video data.
The systems and methods disclosed herein tackle all of the noted problems, and further improve the resultant images by manipulation of the large image's parts (segments). The disclosed systems and method further avoid the difficult processing associated with diffusing error to an adjacent band. In a general sense, the disclosed embodiments include dividing the large image into bands in particular ways, processing these bands in parallel and then putting them back together in an optimal way to create the final processed image. The methods described herein include a combination of some, or all, of the following operations:                1. Overlapping the image bands;        2. Padding the bands with different values and images;        3. Redefining the binary values at the common boundary of the bands.        
Disclosed in embodiments herein is a method for processing an image, comprising: dividing the image into bands; adding to each band additional image data not found in the band; processing the bands to produce processed bands; and recombining the processed bands to produce a processed image.
Also disclosed in embodiments herein is a method for processing a large-format image, comprising: dividing the large format image into N bands; adding to each of said N bands, along at least an edge additional image data not found in said band; processing each of said N bands to produce N processed bands, wherein said N processed bands each include processed image values derived from the additional image data; and recombining the processed bands while eliminating overlapping regions thereof to produce a processed image.
Further disclosed in embodiments herein is a system for processing an image, comprising: an image splitter for dividing the image into bands, each of said bands assigned to a dedicated processing channel; within the channel adding to each band, additional image data not originally found in the band; an image processor for processing all the image data in each band to produce processed bands; and an image stitcher for recombining the processed bands to produce a processed image.